Conventional systems that attempt to assess the trustworthiness of an online activity suffer from various deficiencies when there is insufficient information explicitly available to make such determinations of trustworthiness. These conventional systems, such as scoring systems, fail to fully consider various sources of available information and lack the ability to make accurate inferences from the information, instead requiring frequent manual intervention which introduces inefficiencies and hinders scale. Further, conventional systems fail to recognize the extensive variations in legitimate human behavior and, instead, may identify legitimate, trustworthy people and activities as untrustworthy. As a result, such systems block trustworthy people from legitimate activities. Moreover, conventional systems do not enable timely inclusion of a domain expert's understanding of up-to-date fraud or identity false-pretense techniques, and either fail to identify illegitimate activities or broadly dismiss legitimate ones.